Knowledge Based Neurocomputing

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Knowledge-based Neurocomputing

Author : Ian Cloete
Publisher : MIT Press
ISBN 13 : 9780262032742
Total Pages : 512 pages
Book Rating : 4.0/5 (327 download)

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Book Synopsis Knowledge-based Neurocomputing by : Ian Cloete

Download or read book Knowledge-based Neurocomputing written by Ian Cloete and published by MIT Press. This book was released on 2000 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: Looking at ways to encode prior knowledge and to extract, refine, and revise knowledge within a neurocomputing system.Neurocomputing methods are loosely based on a model of the brain as a network of simple interconnected processing elements corresponding to neurons. These methods derive their power from the collective processing of artificial neurons, the chief advantage being that such systems can learn and adapt to a changing environment. In knowledge-based neurocomputing, the emphasis is on the use and representation of knowledge about an application. Explicit modeling of the knowledge represented by such a system remains a major research topic. The reason is that humans find it difficult to interpret the numeric representation of a neural network.The key assumption of knowledge-based neurocomputing is that knowledge is obtainable from, or can be represented by, a neurocomputing system in a form that humans can understand. That is, the knowledge embedded in the neurocomputing system can also be represented in a symbolic or well-structured form, such as Boolean functions, automata, rules, or other familiar ways. The focus of knowledge-based computing is on methods to encode prior knowledge and to extract, refine, and revise knowledge within a neurocomputing system.ContributorsC. Aldrich, J. Cervenka, I. Cloete, R.A. Cozzio, R. Drossu, J. Fletcher, C.L. Giles, F.S. Gouws, M. Hilario, M. Ishikawa, A. Lozowski, Z. Obradovic, C.W. Omlin, M. Riedmiller, P. Romero, G.P.J. Schmitz, J. Sima, A. Sperduti, M. Spott, J. Weisbrod, J.M. Zurada

Knowledge-Based Neurocomputing: A Fuzzy Logic Approach

Author : Eyal Kolman
Publisher : Springer Science & Business Media
ISBN 13 : 3540880763
Total Pages : 108 pages
Book Rating : 4.5/5 (48 download)

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Book Synopsis Knowledge-Based Neurocomputing: A Fuzzy Logic Approach by : Eyal Kolman

Download or read book Knowledge-Based Neurocomputing: A Fuzzy Logic Approach written by Eyal Kolman and published by Springer Science & Business Media. This book was released on 2009-01-17 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book details the state-of-the-art in knowledge-based neurocomputing. It introduces a novel fuzzy-rule base known as Fuzzy All-permutations Rule-Base (FARB) and presents new connections between artificial neural networks and FARB.

Knowledge-Based Systems

Author : Rajendra Akerkar
Publisher : Jones & Bartlett Learning
ISBN 13 : 0763776475
Total Pages : 375 pages
Book Rating : 4.7/5 (637 download)

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Book Synopsis Knowledge-Based Systems by : Rajendra Akerkar

Download or read book Knowledge-Based Systems written by Rajendra Akerkar and published by Jones & Bartlett Learning. This book was released on 2010-08-30 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge Based Systems (KBS) are systems that use artificial intelligence techniques in the problem solving process. This text is designed to develop an appreciation of KBS and their architecture and to help users understand a broad variety of knowledge based techniques for decision support and planning. It assumes basic computer science skills and a math background that includes set theory, relations, elementary probability, and introductory concepts of artificial intelligence. Each of the 12 chapters are designed to be modular providing instructors with the flexibility to model the book to their own course needs. Exercises are incorporated throughout the text to highlight certain aspects of the material being presented and to stimulate thought and discussion.

Web Data Mining and the Development of Knowledge-Based Decision Support Systems

Author : Sreedhar, G.
Publisher : IGI Global
ISBN 13 : 1522518789
Total Pages : 409 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Web Data Mining and the Development of Knowledge-Based Decision Support Systems by : Sreedhar, G.

Download or read book Web Data Mining and the Development of Knowledge-Based Decision Support Systems written by Sreedhar, G. and published by IGI Global. This book was released on 2016-12-21 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: Websites are a central part of today’s business world; however, with the vast amount of information that constantly changes and the frequency of required updates, this can come at a high cost to modern businesses. Web Data Mining and the Development of Knowledge-Based Decision Support Systems is a key reference source on decision support systems in view of end user accessibility and identifies methods for extraction and analysis of useful information from web documents. Featuring extensive coverage across a range of relevant perspectives and topics, such as semantic web, machine learning, and expert systems, this book is ideally designed for web developers, internet users, online application developers, researchers, and faculty.

AI*IA 2001: Advances in Artificial Intelligence

Author : Associazione italiana per l'intelligenza artificiale. Congress
Publisher : Springer Science & Business Media
ISBN 13 : 3540426019
Total Pages : 408 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis AI*IA 2001: Advances in Artificial Intelligence by : Associazione italiana per l'intelligenza artificiale. Congress

Download or read book AI*IA 2001: Advances in Artificial Intelligence written by Associazione italiana per l'intelligenza artificiale. Congress and published by Springer Science & Business Media. This book was released on 2001-09-12 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the scientific track of the 7th Congress of the Italian Association for Artificial Intelligence, AI*IA 2001, held in Bari, Italy, in September 2001. The 25 revised long papers and 16 revised short papers were carefully reviewed and selected for inclusion in the volume. The papers are organized in topical sections on machine learning; automated reasoning; knowledge representation; multi-agent systems; natural language processing; perception, vision, and robotics; and planning and scheduling.

AI*IA 2001: Advances in Artificial Intelligence

Author : Floriana Esposito
Publisher : Springer
ISBN 13 : 354045411X
Total Pages : 400 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis AI*IA 2001: Advances in Artificial Intelligence by : Floriana Esposito

Download or read book AI*IA 2001: Advances in Artificial Intelligence written by Floriana Esposito and published by Springer. This book was released on 2003-06-30 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the scientific track of the 7th Congress of the Italian Association for Artificial Intelligence, AI*IA 2001, held in Bari, Italy, in September 2001. The 25 revised long papers and 16 revised short papers were carefully reviewed and selected for inclusion in the volume. The papers are organized in topical sections on machine learning; automated reasoning; knowledge representation; multi-agent systems; natural language processing; perception, vision, and robotics; and planning and scheduling.

Neural-Symbolic Learning Systems

Author : Artur S. d'Avila Garcez
Publisher : Springer Science & Business Media
ISBN 13 : 1447102118
Total Pages : 276 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Neural-Symbolic Learning Systems by : Artur S. d'Avila Garcez

Download or read book Neural-Symbolic Learning Systems written by Artur S. d'Avila Garcez and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence is concerned with producing devices that help or replace human beings in their daily activities. Neural-symbolic learning systems play a central role in this task by combining, and trying to benefit from, the advantages of both the neural and symbolic paradigms of artificial intelligence. This book provides a comprehensive introduction to the field of neural-symbolic learning systems, and an invaluable overview of the latest research issues in this area. It is divided into three sections, covering the main topics of neural-symbolic integration - theoretical advances in knowledge representation and learning, knowledge extraction from trained neural networks, and inconsistency handling in neural-symbolic systems. Each section provides a balance of theory and practice, giving the results of applications using real-world problems in areas such as DNA sequence analysis, power systems fault diagnosis, and software requirements specifications. Neural-Symbolic Learning Systems will be invaluable reading for researchers and graduate students in Engineering, Computing Science, Artificial Intelligence, Machine Learning and Neurocomputing. It will also be of interest to Intelligent Systems practitioners and anyone interested in applications of hybrid artificial intelligence systems.

The Handbook of Brain Theory and Neural Networks

Author : Michael A. Arbib
Publisher : MIT Press
ISBN 13 : 0262011972
Total Pages : 1328 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis The Handbook of Brain Theory and Neural Networks by : Michael A. Arbib

Download or read book The Handbook of Brain Theory and Neural Networks written by Michael A. Arbib and published by MIT Press. This book was released on 2003 with total page 1328 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition presents the enormous progress made in recent years in the many subfields related to the two great questions : how does the brain work? and, How can we build intelligent machines? This second edition greatly increases the coverage of models of fundamental neurobiology, cognitive neuroscience, and neural network approaches to language. (Midwest).

Computational Science - ICCS 2002

Author : Peter M.A. Sloot
Publisher : Springer
ISBN 13 : 3540460438
Total Pages : 1097 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Computational Science - ICCS 2002 by : Peter M.A. Sloot

Download or read book Computational Science - ICCS 2002 written by Peter M.A. Sloot and published by Springer. This book was released on 2003-08-01 with total page 1097 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Science is the scienti?c discipline that aims at the development and understanding of new computational methods and techniques to model and simulate complex systems. The area of application includes natural systems – such as biology, envir- mental and geo-sciences, physics, and chemistry – and synthetic systems such as electronics and ?nancial and economic systems. The discipline is a bridge b- ween ‘classical’ computer science – logic, complexity, architecture, algorithms – mathematics, and the use of computers in the aforementioned areas. The relevance for society stems from the numerous challenges that exist in the various science and engineering disciplines, which can be tackled by advances made in this ?eld. For instance new models and methods to study environmental issues like the quality of air, water, and soil, and weather and climate predictions through simulations, as well as the simulation-supported development of cars, airplanes, and medical and transport systems etc. Paraphrasing R. Kenway (R.D. Kenway, Contemporary Physics. 1994): ‘There is an important message to scientists, politicians, and industrialists: in the future science, the best industrial design and manufacture, the greatest medical progress, and the most accurate environmental monitoring and forecasting will be done by countries that most rapidly exploit the full potential ofcomputational science’. Nowadays we have access to high-end computer architectures and a large range of computing environments, mainly as a consequence of the enormous s- mulus from the various international programs on advanced computing, e.g.

Advances in Neural Information Processing Systems 16

Author : Sebastian Thrun
Publisher : MIT Press
ISBN 13 : 9780262201520
Total Pages : 1694 pages
Book Rating : 4.2/5 (15 download)

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Book Synopsis Advances in Neural Information Processing Systems 16 by : Sebastian Thrun

Download or read book Advances in Neural Information Processing Systems 16 written by Sebastian Thrun and published by MIT Press. This book was released on 2004 with total page 1694 pages. Available in PDF, EPUB and Kindle. Book excerpt: Papers presented at the 2003 Neural Information Processing Conference by leading physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The annual Neural Information Processing (NIPS) conference is the flagship meeting on neural computation. It draws a diverse group of attendees -- physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The presentations are interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, brain imaging, vision, speech and signal processing, reinforcement learning and control, emerging technologies, and applications. Only thirty percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains all the papers presented at the 2003 conference.

Sensitivity Analysis for Neural Networks

Author : Daniel S. Yeung
Publisher : Springer Science & Business Media
ISBN 13 : 3642025323
Total Pages : 89 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Sensitivity Analysis for Neural Networks by : Daniel S. Yeung

Download or read book Sensitivity Analysis for Neural Networks written by Daniel S. Yeung and published by Springer Science & Business Media. This book was released on 2009-11-09 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks are used to model systems that receive inputs and produce outputs. The relationships between the inputs and outputs and the representation parameters are critical issues in the design of related engineering systems, and sensitivity analysis concerns methods for analyzing these relationships. Perturbations of neural networks are caused by machine imprecision, and they can be simulated by embedding disturbances in the original inputs or connection weights, allowing us to study the characteristics of a function under small perturbations of its parameters. This is the first book to present a systematic description of sensitivity analysis methods for artificial neural networks. It covers sensitivity analysis of multilayer perceptron neural networks and radial basis function neural networks, two widely used models in the machine learning field. The authors examine the applications of such analysis in tasks such as feature selection, sample reduction, and network optimization. The book will be useful for engineers applying neural network sensitivity analysis to solve practical problems, and for researchers interested in foundational problems in neural networks.

Neural Information Processing

Author : Bao-Liang Lu
Publisher : Springer Science & Business Media
ISBN 13 : 3642249574
Total Pages : 799 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Neural Information Processing by : Bao-Liang Lu

Download or read book Neural Information Processing written by Bao-Liang Lu and published by Springer Science & Business Media. This book was released on 2011-10-26 with total page 799 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three volume set LNCS 7062, LNCS 7063, and LNCS 7064 constitutes the proceedings of the 18th International Conference on Neural Information Processing, ICONIP 2011, held in Shanghai, China, in November 2011. The 262 regular session papers presented were carefully reviewed and selected from numerous submissions. The papers of part I are organized in topical sections on perception, emotion and development, bioinformatics, biologically inspired vision and recognition, bio-medical data analysis, brain signal processing, brain-computer interfaces, brain-like systems, brain-realistic models for learning, memory and embodied cognition, Clifford algebraic neural networks, combining multiple learners, computational advances in bioinformatics, and computational-intelligent human computer interaction. The second volume is structured in topical sections on cybersecurity and data mining workshop, data mining and knowledge doscovery, evolutionary design and optimisation, graphical models, human-originated data analysis and implementation, information retrieval, integrating multiple nature-inspired approaches, Kernel methods and support vector machines, and learning and memory. The third volume contains all the contributions connected with multi-agent systems, natural language processing and intelligent Web information processing, neural encoding and decoding, neural network models, neuromorphic hardware and implementations, object recognition, visual perception modelling, and advances in computational intelligence methods based pattern recognition.

Combinations of Intelligent Methods and Applications

Author : Ioannis Hatzilygeroudis
Publisher : Springer Science & Business Media
ISBN 13 : 3642196187
Total Pages : 170 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Combinations of Intelligent Methods and Applications by : Ioannis Hatzilygeroudis

Download or read book Combinations of Intelligent Methods and Applications written by Ioannis Hatzilygeroudis and published by Springer Science & Business Media. This book was released on 2011-03-29 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: The combination of different intelligent methods is a very active research area in Artificial Intelligence (AI). The aim is to create integrated or hybrid methods that benefit from each of their components. Some of the existing efforts combine soft computing methods either among themselves or with more traditional AI methods such as logic and rules. Another stream of efforts integrates machine learning with soft-computing or traditional AI methods. Yet another integrates agent-based approaches with logic and also non-symbolic approaches. Some of the combinations have been quite important and more extensively used, like neuro-symbolic methods, neuro-fuzzy methods and methods combining rule-based and case-based reasoning. However, there are other combinations that are still under investigation, such as those related to the Semantic Web. The 2nd Workshop on “Combinations of Intelligent Methods and Applications” (CIMA 2010) was intended to become a forum for exchanging experience and ideas among researchers and practitioners who are dealing with combining intelligent methods either based on first principles or in the context of specific applications. CIMA 2010 was held in conjunction with the 22nd IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2010). Also, a special track was organized in ICTAI 2010, under the same title. This volume includes revised versions of the papers presented in CIMA 2010 and one of the short papers presented in the corresponding ICTAI 2010 special track. It also includes a paper of the editors as invited.

Bio-Inspired Systems: Computational and Ambient Intelligence

Author : Joan Cabestany
Publisher : Springer
ISBN 13 : 3642024785
Total Pages : 1356 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Bio-Inspired Systems: Computational and Ambient Intelligence by : Joan Cabestany

Download or read book Bio-Inspired Systems: Computational and Ambient Intelligence written by Joan Cabestany and published by Springer. This book was released on 2009-06-05 with total page 1356 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents the set of final accepted papers for the tenth edition of the IWANN conference “International Work-Conference on Artificial neural Networks” held in Salamanca (Spain) during June 10–12, 2009. IWANN is a biennial conference focusing on the foundations, theory, models and applications of systems inspired by nature (mainly, neural networks, evolutionary and soft-computing systems). Since the first edition in Granada (LNCS 540, 1991), the conference has evolved and matured. The list of topics in the successive Call for - pers has also evolved, resulting in the following list for the present edition: 1. Mathematical and theoretical methods in computational intelligence. C- plex and social systems. Evolutionary and genetic algorithms. Fuzzy logic. Mathematics for neural networks. RBF structures. Self-organizing networks and methods. Support vector machines. 2. Neurocomputational formulations. Single-neuron modelling. Perceptual m- elling. System-level neural modelling. Spiking neurons. Models of biological learning. 3. Learning and adaptation. Adaptive systems. Imitation learning. Reconfig- able systems. Supervised, non-supervised, reinforcement and statistical al- rithms. 4. Emulation of cognitive functions. Decision making. Multi-agent systems. S- sor mesh. Natural language. Pattern recognition. Perceptual and motor functions (visual, auditory, tactile, virtual reality, etc.). Robotics. Planning motor control. 5. Bio-inspired systems and neuro-engineering. Embedded intelligent systems. Evolvable computing. Evolving hardware. Microelectronics for neural, fuzzy and bio-inspired systems. Neural prostheses. Retinomorphic systems. Bra- computer interfaces (BCI). Nanosystems. Nanocognitive systems.

Bio-Inspired Applications of Connectionism

Author : Jose Mira
Publisher : Springer Science & Business Media
ISBN 13 : 3540422374
Total Pages : 875 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Bio-Inspired Applications of Connectionism by : Jose Mira

Download or read book Bio-Inspired Applications of Connectionism written by Jose Mira and published by Springer Science & Business Media. This book was released on 2001-06-05 with total page 875 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes, together with its companion LNCS 2084, the refereed proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001, held in Granada, Spain in June 2001. The 200 revised papers presented were carefully reviewed and selected for inclusion in the proceedings. The papers are organized in sections on foundations of connectionism, biophysical models of neurons, structural and functional models of neurons, learning and other plasticity phenomena, complex systems dynamics, artificial intelligence and cognitive processes, methodology for nets design, nets simulation and implementation, bio-inspired systems and engineering, and other applications in a variety of fields.

Constructive Neural Networks

Author : Leonardo Franco
Publisher : Springer Science & Business Media
ISBN 13 : 3642045111
Total Pages : 296 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Constructive Neural Networks by : Leonardo Franco

Download or read book Constructive Neural Networks written by Leonardo Franco and published by Springer Science & Business Media. This book was released on 2009-10-27 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a collection of invited works that consider constructive methods for neural networks, taken primarily from papers presented at a special th session held during the 18 International Conference on Artificial Neural Networks (ICANN 2008) in September 2008 in Prague, Czech Republic. The book is devoted to constructive neural networks and other incremental learning algorithms that constitute an alternative to the standard method of finding a correct neural architecture by trial-and-error. These algorithms provide an incremental way of building neural networks with reduced topologies for classification problems. Furthermore, these techniques produce not only the multilayer topologies but the value of the connecting synaptic weights that are determined automatically by the constructing algorithm, avoiding the risk of becoming trapped in local minima as might occur when using gradient descent algorithms such as the popular back-propagation. In most cases the convergence of the constructing algorithms is guaranteed by the method used. Constructive methods for building neural networks can potentially create more compact and robust models which are easily implemented in hardware and used for embedded systems. Thus a growing amount of current research in neural networks is oriented towards this important topic. The purpose of this book is to gather together some of the leading investigators and research groups in this growing area, and to provide an overview of the most recent advances in the techniques being developed for constructive neural networks and their applications.

Foundations of Computational Intelligence

Author : Aboul-Ella Hassanien
Publisher : Springer
ISBN 13 : 3642010822
Total Pages : 400 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Foundations of Computational Intelligence by : Aboul-Ella Hassanien

Download or read book Foundations of Computational Intelligence written by Aboul-Ella Hassanien and published by Springer. This book was released on 2009-05-02 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundations of Computational Intelligence Volume 1: Learning and Approximation: Theoretical Foundations and Applications Learning methods and approximation algorithms are fundamental tools that deal with computationally hard problems and problems in which the input is gradually disclosed over time. Both kinds of problems have a large number of applications arising from a variety of fields, such as algorithmic game theory, approximation classes, coloring and partitioning, competitive analysis, computational finance, cuts and connectivity, inapproximability results, mechanism design, network design, packing and covering, paradigms for design and analysis of approxi- tion and online algorithms, randomization techniques, real-world applications, scheduling problems and so on. The past years have witnessed a large number of interesting applications using various techniques of Computational Intelligence such as rough sets, connectionist learning; fuzzy logic; evolutionary computing; artificial immune systems; swarm intelligence; reinforcement learning, intelligent multimedia processing etc. . In spite of numerous successful applications of C- putational Intelligence in business and industry, it is sometimes difficult to explain the performance of these techniques and algorithms from a theoretical perspective. Therefore, we encouraged authors to present original ideas dealing with the inc- poration of different mechanisms of Computational Intelligent dealing with Lea- ing and Approximation algorithms and underlying processes. This edited volume comprises 15 chapters, including an overview chapter, which provides an up-to-date and state-of-the art research on the application of Computational Intelligence for learning and approximation.